Update README.md

README.md

@@ -27,47 +27,14 @@ configs:
   - split: train
     path: data/train-*
 ---
-# Tweets
+# Tweets (Teeny-Tiny Castle)
 
-## Overview 
+This dataset is part of the tutorial tied to the [Teeny-Tiny Castle](https://github.com/Nkluge-correa/TeenyTinyCastle), an open-source repository containing educational tools for AI Ethics and Safety research. 
 
-This dataset contains texts from customers posted on Twitter regarding their air travel experiences,
-whether they were upset, neutral, or satisfied with the trip and the airline's service.
-
-## Dataset Details
-
-The dataset is a smaller version of the original dataset. This data originally came from [Crowdflower's Data for Everyone library](https://data.world/crowdflower)
-The original Twitter data was scraped from February 2015, and contributors were asked first to classify positive, negative, and neutral tweets,
-followed by categorizing negative reasons (such as "late flight" or "rude service").
-This version contains whether the sentiment of the tweets in this set was positive (16%), neutral (21%), or negative (63%) for six US airlines.
-
-- Dataset Name: [Twitter US Airline Sentiment](https://www.kaggle.com/datasets/crowdflower/twitter-airline-sentiment)
-- Language:  English
-- Total Size: 14,640  demonstrations
-
-## Contents
-
-The dataset consists of a data frame with the following columns:
-
-- label
-- text
-
-```bash
-{
-  "label": 0,
-  "text": "virginamerica why are your first fares in may over three times more than other carriers when all seats are available to select.",
-}
-```
-
-## How to use
+## How to Use
 
 ```python
 from datasets import load_dataset
 
-dataset = load_dataset("AiresPucrs/tweets", split='train')
-
+dataset = load_dataset("AiresPucrs/tweets", split = 'train')
 ```
-
-## License
-
-The Twitter US Airline Sentiment is licensed under the [Creative Commons(CC)](https://creativecommons.org/licenses/by-nc-sa/4.0/) License CC BY-NC-SA 4.0.